fireworks_list_usersList account members (users). Control-plane: GET /v1/accounts/{account_id}/users.
| Name | Required | Description | Default |
|---|---|---|---|
| pageSize | No | Page size (max 200). | |
| pageToken | No | Opaque page token from a previous response's nextPageToken. | |
| account_id | No | Fireworks account id. Overrides FIREWORKS_ACCOUNT_ID for this call. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation indicates readOnlyHint: true, and the description adds the HTTP method and path, confirming a read-only operation. It does not contradict annotations and provides additional context beyond them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, the first stating the purpose and the second providing the API endpoint. No extraneous information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not mention the return format (e.g., list of user objects, pagination behavior) despite the schema including pagination parameters. For a list tool, this omission reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented in the schema. The description implicitly links account_id to the URL path, adding some semantic context beyond the schema, justifying above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists account members (users) and provides the specific HTTP method and path, effectively distinguishing it from sibling list tools like fireworks_list_datasets and fireworks_list_models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when to list users instead of deployments or datasets. The description does not include any when-to-use or when-not-to-use indicators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a distinct resource and action combination (e.g., create_dataset vs delete_deployment vs list_models), with no overlapping purposes. Descriptions clearly differentiate each tool.
All tools follow a consistent 'fireworks_verb_noun' pattern, with verbs like create, delete, get, list and singular or plural nouns as appropriate. No mixing of conventions.
14 tools cover the main resources of the Fireworks platform (accounts, datasets, deployments, fine-tuning jobs, models, batch inference, users). The scope is appropriate and not overwhelming.
The tool set is heavily read-oriented with only one creation tool (create_dataset) and one deletion tool (delete_deployment). Missing create for deployments, fine-tuning jobs, models; missing update and delete for most resources. Gaps would hinder full workflow automation.